1. Field of the Invention
This invention relates to velocity estimation using doppler ultrasound techniques, and more particularly to a spatial vector averaging method and apparatus for estimating blood flow velocities in an ultrasound medical diagnostic imaging system.
2. Description of the Related Art
Medical diagnostic ultrasound systems generate images of anatomical structures within a patient's body by scanning a target area with ultrasound signals. Typically, ultrasound signals on the order of typically 3.0 MHZ are transmitted into a patient. Returning echo signals then are formed into a beam-pattern and analyzed to convey image and/or flow characteristics of the scanned area.
Doppler Ultrasound
Doppler ultrasound is the field of detection, quantization, and medical evaluation of tissue motion and blood flow. Specifically, doppler ultrasound is used to determine the presence or absence of flow, the direction and speed of flow, and the character of flow. Continuous wave doppler ultrasound (i.e., cw-doppler) uses continuous-wave ultrasound signals. Pulsed doppler ultrasound uses pulsed-wave ultrasound signals. Applications of doppler ultrasound are found in virtually all medical specialties, including cardiology, neurology, radiology, obstetrics, pediatrics and surgery.
Doppler ultrasound is based upon the doppler effect, which is a change in frequency caused by the relative motion among a wave source, receiver and reflector. As applied to medical applications, an ultrasound transducer embodying the source and receiver is stationary, while blood or tissue fluid is the moving reflector. The change in frequency detected is the difference between the transmitted ultrasound signal frequency and the reflected ultrasound signal frequency. Such change is a function of the transmitted signal frequency, the propagation speed of the transmitted signal through the patient's anatomy, the speed of flow in the range gate and the angle of incidence between the ultrasound signal and the direction of blood flow.
A doppler ultrasound instrument includes a voltage generator (e.g., oscillator) with an oscillator gate that generates electrical signal inputs to a transducer. The oscillator gate allows respective pulses of several voltage cycles to pass to the transducer for conversion into respective ultrasound pulses. Ultrasound pulses used for doppler have minimum pulse lengths of approximately five cycles and typical pulse lengths of 25-30 cycles. The multiple cycles within a pulse are used to determine the doppler shift of returning echoes. Voltage pulses resulting from received echoes are processed in a receiver, where they are amplified and compared in frequency with the transmitted signal.
The echoes sensed at the transducer undergo spectral analysis of frequency components. Typically, several frequency components are present. If all flow within a range gate is of a uniform speed and direction, then there is one frequency component. The character of flow in vessels, however, is determined by the vessel size and the uniformity of its walls. Changes in size, turns and abnormalities, such as the presence of plaques and stenoses, alter the character of the flow. Conventionally, flow is characterized as plug, laminar, parabolic, disturbed, and turbulent. Accordingly, portions of flow often are moving at different speeds and, sometimes, in different directions. Thus, many different doppler shifts, and thus frequency components, occur.
In certain instances, artifacts occur in doppler ultrasound. Artifacts as used herein are anything that is not properly indicative of the structures of the flows imaged or sampled. More specifically, artifacts are incorrect presentations of flow or image information. Artifacts are caused by some characteristic of the sampling or imaging technique. Although other imaging and doppler artifacts occur, addressed here is a common doppler ultrasound artifact known as aliasing.
Aliasing is the improper representation of information that has been insufficiently sampled. The sampling can be of a spatial or temporal nature. As the sampling rate is reduced, for example, the ability to resolve the details of an object, then the general character of the object, is lost. In cases this results in the object being mischaracterized (e.g., having a false appearance or assumed identity--an alias). An example of temporal aliasing occurs in, for example, a rotating object such as a fan. The blades of the fan are observed to rotate at various speeds and in reverse directions when viewed with a strobe light flashing at various rates.
The Nyquist limit or Nyquist frequency describes the minimum sampling rate required to avoid aliasing. Specifically, there must be at least two samples per period of the wave being observed. For a complicated signal, such as a doppler echo signal containing many frequencies, it is preferable that the sampling rate be sufficient to include at least two samples for each period of the highest doppler-shift frequency present. Stated differently, if the highest doppler-shift frequency present in a signal exceeds one half the pulse repetition frequency, then aliasing occurs. On a doppler spectral display, frequency aliasing is manifested as a "wrapping around" of the spectrum so that blood of high velocity in one direction instead appears to be going in the opposite direction. This invention addresses anti-aliasing in noisy environments.
Doppler Velocity Estimation Methods
One known method for velocity display is to use Fast Fourier Transform ("FFT") techniques to process the echo signals reflected from a target volume so as to generate a numerical display. This method is severely limited because velocity is determined only for a small sample volume. Real-time imaging estimating velocity in an area larger than the sample volume is highly desirable.
Doppler velocity estimators often use time domain processing techniques in which a series of N repetitive pulses separated by time periods, T, are transmitted toward a moving target along a given scan direction. Other than FFT, other time-domain approaches use zero-crossing estimators or autocorrelation (pulse-pair) algorithms.
The autocorrelation function of a digitized doppler signal is given by equation (1): ##EQU1## where, T=pulse repetition interval;
n=n-th pulse; PA1 N=number of temporal samples averaged; PA1 .DELTA.=time interval in spatial direction; PA1 m=m-th time interval; and PA1 z=pulse doppler echo. PA1 N=the number of temporal samples averaged.
The autocorrelation occurs as the temporal averaging over N time periods of an m-th sample and the same m-th sample at a prior time period (n-1)T. The maximum detectable doppler frequency that can be detected from the phase of Equation (1) is limited to one-half the pulse repetition frequency (i.e., 1/(2T)). Although autocorrelation is recognized as providing the best real-time performance of these time-domain approaches, it suffers from a relatively low frame rate and the need for many echoes to estimate slower blood-flow velocities. It also results in the usual pulse doppler aliasing limitation. Inventors J. Kim and D. C. Liu describe a modified autocorrelation method in "Modified Autocorrelation Method Compared With Maximum Entropy Method and RF Cross-Correlation Method as Mean Frequency Estimator for Doppler Ultrasound," 1991 Ultrasonics Symposium; (IEEE 1051-0117/91/0000-1285, pages 1285-1290) Therein they describe an autocorrelation process with an added spatial averaging dimension.
Their modified autocorrelation function of a digitized doppler signal is given by equation (2): ##EQU2## where, M=the number of spatial samples averaged;
In this 2-dimensional spatial-temporal velocity estimation procedure, N data samples are averaged over the doppler time after the formation of the pulse-pair signal. The resultant vectors then are averaged in the spatial vector domain. Such modified autocorrelation procedure improves anti-aliasing performance in highly noisy environments. Such improvement is based upon the averaging out of amplitude fluctuations in the noisy environment.
Terminology
Pulse-pair, as used herein, refers to the pair of echo signals being autocorrelated. Equations (1) and (2) above each use the following two signals as the pulse pair: EQU z[nT,m.DELTA.] EQU z*[(n-1)T,m.DELTA.]
Temporally-displaced pulse-pair, as used herein, refers to the relation of the two echo signals forming the pulse-pair. Note that z and z* correspond to the same spatially-located sample m.DELTA., but at different times nT and (n-1)T. Thus, the pulse-pair are temporally-displaced.
Temporal averaging, as used herein, refers to autocorrelating the pulse-pairs over time. In equations (1) and (2) above the pulse-pairs are temporally averaged over N samples, as indicated by: ##EQU3##
Spatial averaging, as used herein, refers to autocorrelating the pulse-pairs over a spatial dimension. In equation (2) above, the pulse-pairs are spatially averaged over M samples, as indicated by: ##EQU4##
Spatial-temporal averaging and temporal-spatial averaging, as used herein refer to autocorrelating the pulse-pairs over both time and space. Thus, in equation (2) above, the pulse-pairs are spatial-temporal averaged over M spatial samples and N temporal samples, as indicated by: ##EQU5##